Abstract
Although they clearly exist, affinities among individuals are not all easily identified. Yet, they offer unique opportunities to discover new social networks, strengthen ties among individuals, and provide recommendations. We propose the idea of Implicit Affinity Networks (IANs) to build, visualize, and track affinities among groups of individuals. IANs are simple, interactive graphical representations that users may navigate to uncover interesting patterns. This thesis describes a system supporting the construction of IANs and evaluates it in the context of family history and online communities.
Degree
MS
College and Department
Physical and Mathematical Sciences; Computer Science
Rights
http://lib.byu.edu/about/copyright/
BYU ScholarsArchive Citation
Smith, Matthew Scott, "Implicit Affinity Networks" (2007). Theses and Dissertations. 1112.
https://scholarsarchive.byu.edu/etd/1112
Date Submitted
2007-01-05
Document Type
Thesis
Handle
http://hdl.lib.byu.edu/1877/etd1682
Keywords
communities, social network analysis, collaboration, community evolution, affinities, family history, business intelligence, recommendation systems, computer science
Language
English